 | M. de Almeida, C. Samarawickrama, N. de Silva, G. Ratnayaka, and S. Perera
The 23rd International Conference on Information Integration and Web Intelligence, 2021, pp. 259--266, [pdf] [bib]
Law and order is a field that can highly benefit from the contribution of Natural Language Processing (NLP) to its betterment. An area in which NLP can be of immense help is, information retrieval from legal documents which function as legal databases. The extraction of legal parties from the aforementioned legal documents can be identified as a task of high importance since it has a significant impact on the proceedings of contemporary legal cases. This study proposes a novel deep learning methodology which can be effectively used to find a solution to the problem of identifying legal party members in legal documents. In addition to that, in this paper, we introduce a novel data set which is annotated with legal party information by an expert in the legal domain. The deep learning model proposed in this study provides a benchmark for the legal party identification task on this data set. Evaluations for the solution presented in the paper show that our system has 90.89\% precision and 91.69\% recall for an unseen paragraph from a legal document, thus conforming the success of our attempt. |
